Triple

T17590481
Position Surface form Disambiguated ID Type / Status
Subject El Beida E428432 entity
Predicate roadConnection P385 FINISHED
Object Tobruk NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tobruk | Statement: [El Beida, roadConnection, Tobruk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tobruk
Context triple: [El Beida, roadConnection, Tobruk]
  • A. Tobruk chosen
    Tobruk is a strategic port city on Libya’s Mediterranean coast that gained historical significance as the site of major World War II battles and sieges.
  • B. Bengasi
    Bengasi is a metro station on the Turin Metro system in Turin, Italy.
  • C. Kasserine
    Kasserine is a city in west-central Tunisia known for its role as a major center of protest and unrest during the Tunisian Revolution.
  • D. Tobruk District
    Tobruk District is an administrative region in eastern Libya centered on the port city of Tobruk, known for its strategic coastal location and historical significance.
  • E. Sirte, Libya
    Sirte, Libya is a coastal city on the Mediterranean Sea that gained international prominence as Muammar Gaddafi’s final stronghold and the site of his death during the 2011 Libyan civil war.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469e6e3888190b73a5b6d7e8c0a55 completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 5:51 a.m.